Artificial Intelligence for healthcare Professionals - Part 2: Advanced Applications and Responsible Integration

Healthcare professionals

Professional background in healthcare
Prior particpation in the course Artificial Intelligence for Healthcare Professionals – Part 1 , or equivalent knowledge.
No technical or programming background required

As Artificial Intelligence becomes more deeply integrated into healthcare systems, its role extends beyond diagnostics and decision support into more complex domains such as immersive therapeutic environments, biosensing technologies, telemedicine infrastructures, and human–AI collaborative systems.

This training explores the next layer of AI in healthcare, focusing on how advanced technologies are reshaping clinical practice and enabling new forms of care delivery. Participants are introduced to immersive systems such as Virtual Reality and Augmented Reality used in rehabilitation and therapy, as well as biosensing technologies that capture physiological and behavioral signals to support clinical assessment.

The course also examines telemedicine and remote healthcare systems, including AI-supported remote diagnostics and tele-operated medical procedures. These developments are contextualized within a broader framework of human-centered AI, where clinicians remain central in interpreting, supervising, and guiding AI-supported systems. Real-world case studies demonstrate applications in mental healthcare, including emotion-aware systems and AI-supported therapeutic interventions such as art-based therapy approaches. These examples illustrate how AI can support clinicians in delivering more personalized and context-aware care while maintaining professional oversight.

Finally, the course addresses ethical, regulatory, and safety considerations, including GDPR, the EU AI Act, and clinical accountability in AI-supported healthcare systems.

This module is is Part 2 of the course, and is also structured over two days:

Day 1: Emerging Technologies in Healthcare

Immersive Technologies in Healthcare

• Virtual Reality (VR), Augmented Reality (AR), and Extended Reality (XR)
• Applications in surgical training, rehabilitation, and therapy
• Interactive medical environments and simulation

Biosensing and Neurotechnology

• Brain–computer interfaces (BCI) with EEG & fNIRS
• Eye tracking and physiological monitoring
• AI in Affective computing with physiological sensing
• Objective measurement of cognitive and behavioral responses with AI

Telemedicine and Remote Healthcare

• AI in telemedicine platforms and digital health ecosystems
• AI-supported remote diagnostics
• tele-robotic systems and remote surgical technologies case study and remote interaction demo & workshop

Human-Centered Artificial Intelligence (HCAI)

• Human agency, transparency, ethics, and accountability
• Human-centered recommender systems
• Case studies in art, culture, and multi-stakeholder personalization

Day 2: Responsible AI and the Future of Healthcare

Human-Centered Artificial Intelligence

• clinician–AI collaboration
• explainability and transparency
• avoiding automation bias

Ethical and Regulatory Frameworks

• GDPR, HIPPA and healthcare data protection
• EU AI Act and medical device regulations
• accountability and responsible system design

Case Studies in AI for Healthcare

Examples include:

• AI-assisted diagnostics (AI in Radiology)
• digital therapeutics and rehabilitation systems
• Tele-operation
• AI-supported mental healthcare
• creative therapeutic approaches such as art-based interventions

Future Directions in AI for Healthcare

• AI-augmented clinical environments (Immersive show case XR)
• intelligent hospitals and healthcare ecosystems
• emerging trends in digital medicine and healthcare innovation

By the end of the course, participants will be able to:

• Understand advanced AI applications in healthcare
• Evaluate emerging technologies such as immersive systems and biosensing
• Understand human-centered AI and clinician–AI collaboration
• Assess risks and limitations of advanced AI systems
• Navigate ethical and regulatory requirements
• Critically reflect on future AI-enabled healthcare systems

Two-day intensive training combining:

• lectures and advanced concepts
• demonstrations of technologies
• case studies and applied discussions
• interactive sessions

Certificate of attendance

This training builds on foundational knowledge of Artificial Intelligence in healthcare and explores advanced applications, emerging technologies, and responsible integration into clinical practice.